The results from both tasks indicate that people anticipate their future motor performance so as to make decisions that will improve their expected future reward.The relationship between plant traits and species relative abundance along environmental gradients can provide important insights on the determinants of community structure. Here we bring extensive data on six key traits (specific leaf area (SLA), seed mass, seed germination rate, height, leaf proline content and photosynthesis rate) to test trait-abundance relationships in a successional chronosequence of subalpine meadow plant communities. Our results show that in late-successional meadows, abundant species had higher values for seed mass, seed germination rate, and SLA, but had lower values for height, photosynthesis rate, and leaf proline content than rarer species. The opposite patterns of trait-abundance relationships were observed for early-successional meadows. Observations of strong trait convergence and divergence in these successional communities lend greater support for niche processes compared to neutral community assembly. We conclude that species’ niches that determine plant growth (plant height and photosynthesis rate), carbon balance (SLA, photosynthesis rate), regeneration (seed mass and seed germination rate), and abiotic stress resistance (leaf proline content) under different environmental conditions have strong influence on species relative abundance in these sub-alpine meadow communities during succession.Periodontal disease, the most prevalent infectious disease in the world, is caused by biofilms formed in periodontal pockets. No specific bacterial species that can cause periodontitis alone has been found in any study to date. Several periodontopathic bacteria are associated with the progress of periodontal disease. Consequently, it is hypothesized that dysbiosis of subgingival microbiota may be a cause of periodontal disease. This study aimed to investigate the relationship between the subgingival microbiota and the clinical status of periodontal pockets in a quantitative and clinically applicable way with the newly developed Oral Care Chip. The Oral Care Chip is a DNA microarray tool with improved quantitative performance, that can be used in combination with competitive PCR to quantitatively detect 17 species of subgingival bacteria. Cluster analysis based on the similarity of each bacterial quantity was performed on 204 subgingival plaque samples collected from periodontitis patients and healthy volunteeCare Chip could be effective at detecting dysbiosis.Salmonella enterica serovar Enteritidis is a major cause of foodborne disease in Uruguay since 1995. We used a genomic approach to study a set of isolates from different sources and years. Whole genome phylogeny showed that most of the strains are distributed in two major lineages (E1 and E2), both belonging to MLST sequence type 11 the major ST among serovar Enteritidis. Strikingly, E2 isolates are over-represented in periods of outbreak abundance in Uruguay, while E1 span all epidemic periods. Both lineages circulate in neighbor countries at the same timescale as in Uruguay, and are present in minor numbers in distant countries. We identified allelic variants associated with each lineage. Three genes, ycdX, pduD and hsdM, have distinctive variants in E1 that may result in defective products. Another four genes (ybiO, yiaN, aas, aceA) present variants specific for the E2 lineage. Overall this work shows that S. enterica serovar Enteritidis strains circulating in Uruguay have the same phylogenetic profile than strains circulating in the region, as well as in more distant countries. Based on these results we hypothesize that the E2 lineage, which is more prevalent during epidemics, exhibits a combination of allelic variants that could be associated with its epidemic ability.The etiologic pathways leading to neuropsychiatric diseases remain poorly defined. As genomic technologies have advanced over the past several decades, considerable progress has been made linking neuropsychiatric disorders to genetic underpinnings. Interest and consideration of nongenetic risk factors (e.g., lead exposure and schizophrenia) have, in contrast, lagged behind heritable frameworks of explanation. Thus, the association of neuropsychiatric illness to environmental chemical exposure, and their potential interactions with genetic susceptibility, are largely unexplored. In this review, we describe emerging approaches for considering the impact of chemical risk factors acting alone and in concert with genetic risk, and point to the potential role of epigenetics in mediating exposure effects on transcription of genes implicated in mental disorders. We highlight recent examples of research in nongenetic risk factors in psychiatric disorders that point to potential shared biological mechanisms-synaptic dysfunction, immune alterations, and gut-brain interactions. We outline new tools and resources that can be harnessed for the study of environmental factors in psychiatric disorders. These tools, combined with emerging experimental evidence, suggest that there is a need to broadly incorporate environmental exposures in psychiatric research, with the ultimate goal of identifying modifiable risk factors and informing new treatment strategies for neuropsychiatric disease.Major depressive disorder with psychotic features (psychotic depression) is a severe disorder. Compared with other psychotic disorders such as schizophrenia, relatively few studies on the neurobiology of psychotic depression have been pursued. Neuroimaging studies investigating psychotic depression have provided evidence for distributed structural brain abnormalities implicating the insular cortex and limbic system. We examined structural brain networks in participants (N = 245) using magnetic resonance imaging. This sample included healthy controls (n = 159) and the largest cross-sectional sample of patients with remitted psychotic depression (n = 86) collected to date. All patients participated in the Study of Pharmacotherapy of Psychotic Depression II randomized controlled trial. We used a novel, whole-brain, data-driven parcellation technique-non-negative matrix factorization-and applied it to cortical thickness data to derive structural covariance networks. Dactolisib We compared patients with remitted psychotic depression to healthy controls and found that patients had significantly thinner cortex in five structural covariance networks (insular-limbic, occipito-temporal, temporal, parahippocampal-limbic, and inferior fronto-temporal), confirming our hypothesis that affected brain networks would incorporate cortico-limbic regions.